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International Conference on Autonomous Unmanned Systems, ICAUS 2021

作者： Ye, Pengpeng Wei, Jianing Lu, Yu Li, Feifei Lin, Tao Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9789811694912

The salvo attack of multi-missile is investigated, where the communication topology is randomly switching and unsustainably connected due to the unreliable links, and the probability of the packet loss is unavailable. Based on feedback linearization, a cooperative guidance protocol is developed in a fully distributed manner, in which gains can be designed incongruently for all missiles, and only the local topology information is essential. Multiple missiles disconnect with each other once the consensus of impact time is reached, and are guided to the target under the proportional navigation guidance (PNG) law individually. Sufficient conditions are established to guarantee the consensus of impact time. A simulation experiment is delivered to validate the effectiveness of the obtained results. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feedback linearization

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Self-Organized Criticality in C. Elegans Neural Network 42

Self-Organized Criticality in C. Elegans Neural Network

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42nd Chinese control Conference, CCC 2023

作者： Gu, Xiao Liu, Jian Yuan, Ye Zhao, Peng Xin, Kuankuan Fang, Tao Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Shanghai Engineering Research Centre of Intelligent Control and Management Shanghai200240 China Institute of Machine Intelligence University of Shanghai for Science and Technology Shanghai200093 China Queensland Brain Institute The University of Queensland BrisbaneQLD4072 Australia

ISBN: (纸本)9789887581543

The self-organized criticality is a fundamental property for organisms to perform normal functional activities. Extensive large-scale biological neural network researches have found the existence of self-organized criticality through avalanche phenomenon, which is typical characteristic of self-organized criticality. However, such research method is not suitable for small-scale biological neural network, because number of neurons in small-scale biological neural network is not large enough to support the emergence of avalanche phenomenon. It has been demonstrated that branching parameter can also be used to describe the propagation of activity in the neural network. Here, in this paper, the C. elegans neural network composed of 302 neurons is selected to investigate the existence of self-organized criticality using branching parameter. Based on the obtained connectome of C. elegans, a directed graph model is constructed to simulate the gradient potential of neurons and the activity of C. elegans, then, the existence of self-organized criticality in the neural network of C. elegans is proved by using branching parameter method. Meanwhile, the result is further confirmed by analyzing the calcium activity data of C. elegans obtained from biological experiments. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Calcium

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Exact Noise-Robust Distributed Gradient-Tracking Algorithm for Constraint-Coupled Resource Allocation Problems

Exact Noise-Robust Distributed Gradient-Tracking Algorithm f...

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IEEE Conference on Decision and control

作者： Wenwen Wu Shanying Zhu Shuai Liu Xinping Guan Department of Automation Shanghai Jiao Tong University Shanghai China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China School of Control Science and Engineering Shandong University Jinan China

The Industrial Internet of Things (1IoT) gradually becomes a new paradigm for information exchange in the industrial production environment. To ensure the high reliability of IloT services, an efficient resource allocation method with good robustness is urgently needed under complex industrial environments. This paper considers the distributed constraint- coupled resource allocation problem with noisy information exchange over an undirected network, where each agent holds a private cost function and obtains the solution via only local communications. Communication noise poses a challenge to gradient-tracking based algorithm as the impact of noise will accumulate and its variance tends to infinity when the noise is persistent. Adopting noise-tracing scheme, we propose an exact noise-robust distributed gradient-tracking algorithm to achieve cost-optimal distribution of resources, which can avoid noise-accumulation in the tracking step. Moreover, noise suppression parameters are introduced to further attenuate the impact of noise. With diminishing suppression parameters, it is theoretically proved that the proposed algorithm is able to achieve exact convergence to the optimal solution. Finally, a numerical example is provided for verification.

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Blockchain-based peer to peer energy trading using distributed model predictive control

Blockchain-based peer to peer energy trading using distribut...

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European control Conference (ECC)

作者： Manuel Sivianes Ascensió n Zafra-Cabeza Carlos Bordons Systems Engineering and Automatic Control Department School of Engineering Universidad de Sevilla Seville Spain System Engineering and Automation Department School of Engineering Universidad de Sevilla Seville Spain Systems Engineering and Automatic Control Department ENGREEN Laboratory of Engineering for Energy and Environmental Sustainability Universidad de Sevilla Seville Spain

ISBN: (数字)9783907144077

ISBN: (纸本)9781665497336

The energy network is experiencing a decentralizing process due to the recent inclusion of distributed energy resources (DERs), such as photovoltaics (PV), electric vehicles (EV), or batteries. This paradigmatic shift involves new challenges that require enhancing the electricity system's flexibility while preserving its integrity and stability. One way of dealing with them is by unbundling the electrical network into smaller, more manageable units, known as microgrids (MG). Nonetheless, the usage of distributed architectures leads to more exchanged data and control information between end agents, involving security or privacy issues. In this context, blockchain technology emerges as a feasible solution that promises transparent, tamper-proof, and safe systems in a decentralized ecosystem. This paper proposes a distributed energy management platform that takes full advantage of the blockchain technology to enable safe peer to peer (P2P) transactions. A Distributed model predictive control (DMPC) scheme is adopted, and its performance is compared with the centralized approach.

关键词： Photovoltaic systems Smart contracts Microgrids Prediction algorithms Stability analysis Blockchains Peer-to-peer computing

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A Two-Stage Stochastic Misocp Method for Planning Source-Grid-Load-Storage Flexibility Resources Considering Flexible Ramp Capacity

SSRN

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SSRN 2024年

作者： Wang, Jinpeng Zeng, Pingliang Yin, Lulu Dong, Yanfei Liu, Xiaofang School of Electrical and Control Engineering Henan University of Urban Construction Pingdingshan China Pinggao Group CO. LTD Pingdingshan China Department of Automation Hangzhou Dianzi University Hangzhou China

With rapidly increasing levels of renewable energy penetration, flexibility resources play an ever more critical role in the future power system. This paper describes a two-stage stochastic mixed integer second order cone (MISOC) method for flexibility resource planning (VFRP) considering source-grid-load-storage interactions. Considering renewable energy penetration levels and flexibility resource characteristics, this study quantifies the extent to which the share of renewable energy generation affects cost performance, and assesses the priority and potential of investing in flexibility resources. Moreover, the multi-type flexibility resource portfolio allocation method and energy storage only approach are compared in terms of socio-economic benefits. A multi-cut Benders-based approach is used for decomposing large-scale stochastic expansion planning problems to reduce the computational burden. Numerical simulation tests on the modified energy test systems I39G20 and F213G20 verified the correctness and effectiveness of the proposed flexible resource planning models and solution algorithms. The simulation results show that retrofit of coal-fired units for better flexibility has a higher investment return. Still, energy storage presents a tremendous investment prospect and potential. Finally, the multi-type flexibility resource portfolio allocation method is more cost-effective than an energy storage only approach. © 2024, The Authors. All rights reserved.

关键词： Energy storage

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A GM-TCN based Hybrid Prediction Method for Ash Fouling Prediction in Coal-fired Power Plant Boiler

A GM-TCN based Hybrid Prediction Method for Ash Fouling Pred...

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2022 Chinese automation Congress, CAC 2022

作者： Shi, Yuanhao Han, Tianxiang Cui, Fangshu Wen, Jie Qiao, Gangzhu North University of China School of Electrical and Control Engineering Taiyuan China Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China North University of China School of Data Science and Technology Taiyuan China

ISBN: (纸本)9781665465335

In response to the problem that ash deposition in boilers has a great impact on production efficiency as well as production safety, a grey level theory prediction model based on time convolution networks (GM-TCN) is proposed to predict the degree of ash in boiler heated areas by using a cleaning factor to assess the ash deposition condition on the heated surfaces. The accuracy of the prediction model is improved by utilizing the features of grey level theory that can predict the developmental changes in system behavior, combined with the high-precision approximation capability of the time-convolutional network. The modelling prediction of the ash level in the heated area of boilers during the production of coal-fired power stations is investigated. Experiments demonstrate that the model can predict the cleanliness factor with high accuracy, and the predicted values are closest to the true values compared to the other two models, verifying the accuracy and reliability of the model. © 2022 IEEE.

关键词： Convolution

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2M3DF: Advancing 3D Industrial Defect Detection with Multi Perspective Multimodal Fusion Network

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Asad, Mujtaba Azeem, Waqar Jiang, He Mustafa, Hafiz Tayyab Yang, Jie Liu, Wei Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Department of Automation Shanghai200240 China Lahore Garrison University Department of Software Engineering Lahore54000 Pakistan China University of Mining and Technology School of Information and Control Engineering Jiangsu Xuzhou221116 China Zhejiang Normal University School of Computer Science and Technology Jinhua321004 China

In the context of Industrial Anomaly Detection (IAD), ensuring the quality of manufactured products is critical. Traditional 2D based methods often fail to capture anomalies present in complex 3D shapes. For effective anomaly detection in 3D shapes, it is essential to incorporate global semantic context, local geometric structure, and color information of the object. To fully leverage these features, we propose a network named 2M3DF, that leverages knowledge from multi-view RGB images and corresponding point cloud information for enhanced anomaly detection performance. Our model initially employs pre-trained feature extractors that generate local features from multi-view RGB images and corresponding point clouds. The novel inter-modality feature representation and fusion module first adapts these inter-modality features and then effectively aligns and aggregates these multimodality features on a pixel-to-point basis. To learn the normality from point-wise fused multimodal features, we fit a multivariate Gaussian distribution to model the normal feature distribution. Comprehensive experimental evaluations using the MVTec3D-AD and Eyecandies dataset validate the effectiveness of our propose model and demonstrate significant improvements in comparison to existing state-of-the-art methods. Our model achieves a 96.6% mean I-AUROC while delivering real-time results. © 1991-2012 IEEE.

关键词： Normal distribution

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A Swarm Model for Target Capturing in a Polygonal Strip

A Swarm Model for Target Capturing in a Polygonal Strip

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Antonio Bono Luigi D' Alfonso Giuseppe Fedele Veysel Gazi Department of Informatics Modeling Electronics and Systems Engineering University of Calabria Rende Italy Department of Control and Automation Engineering Faculty of Electrical and Electronics Engineering Yildiz Technical University Esenler Turkey

This paper presents a methodology to generate proper state trajectories of a swarm of agents, described as a single integrator model. The main goal of the proposed methodology is to route the agents into planar polygons like areas, so that to accomplish for cooperative perimeter surveillance or target capturing tasks. In particular, the agents are driven into a polygonal strip defined by a given containment external convex polygonal region and an internal forbidden convex polygonal region around a prescribed target. The control law is designed looking at a circular strip, then a conversion from circular to polygonal areas is applied to achieve the prescribed goal. Steady-state conditions are analyzed and sufficient conditions derived in terms of the control law parameters. Simulation results put in light the main properties of the resulting kinematic state description.

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Complex Permeability Determination for EE Core Based on Flexible PCB Fixture and Magnetic Flux Path Length Analysis

Complex Permeability Determination for EE Core Based on Flex...

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China Power Supply Society Electromagnetic Compatibility Conference (CPEMC)

作者： Huamin Jie Zhenyu Zhao Yongqi Chang Changdong Wang Shiqi Jiang Richard Xian-Ke Gao Kye Yak See School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China A*STAR Institute of High Performance Computing Singapore Singapore

ISBN: (数字)9798331509552

ISBN: (纸本)9798331509569

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz.

关键词： Magnetic flux Accuracy Flexible printed circuits Magnetic cores Fixtures Electromagnetic interference Permeability measurement Length measurement Permeability Inductors

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Temperature Gradient Analyses of a Tubular Solid Oxide Fuel Cell Fueled by Methanol

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Transactions of Tianjin University 2023年第1期29卷 14-30页

作者： Qidong Xu Meiting Guo Lingchao Xia Zheng Li Qijiao He Dongqi Zhao Keqing Zheng Meng Ni Department of Building and Real Estate Research Institute for Sustainable Urban Development(RISUD)&Research Institute for Smart Energy(RISE)The Hong Kong Polytechnic UniversityHong Kong 999077China School of Artifi cial Intelligence and Automation Key Laboratory of Image Processing and Intelligent ControlHuazhong University of Science and TechnologyWuhan 430074China School of Low-Carbon Energy and Power Engineering China University of Mining and TechnologyXuzhou 221116China

Thermal management in solid oxide fuel cells(SOFC)is a critical issue due to non-uniform electrochemical reactions and convective fl ows within the ***,a 2D mathematical model is established herein to investigate the thermal responses of a tubular methanol-fueled *** show that unlike the low-temperature condition of 873 K,where the peak temperature gradient occurs at the cell center,it appears near the fuel inlet at 1073 K because of the rapid temperature rise induced by the elevated current *** the large heat convection capacity,excessive air could not eff ectively eliminate the harmful temperature gradient caused by the large current ***,optimal control of the current density by properly selecting the operating potential could generate a local thermal neutral ***,the maximum axial temperature gradient could be reduced by about 18%at 973 K and 20%at 1073 K when the air with a 5 K higher temperature is ***,despite the higher electrochemical performance observed,the cell with a counter-fl ow arrange-ment featured by a larger hot area and higher maximum temperature gradients is not preferable for a ceramic SOFC system considering thermal ***,this study could provide insightful thermal information for the operating condition selection,structure design,and stability assessment of realistic SOFCs combined with their internal reforming process.

关键词： Solid oxide fuel cell Modeling Methanol fuel Temperature gradient Internal reforming

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